Silentis White Paper

Privacy-Focused open-source Offline AI Software Powered by open-source models

Executive Summary

Silentis is a privacy-focused open-sourced offline AI software built on Llama 3.2 4B (For now in v0.74), designed to operate without an internet connection. The software is lightweight, standalone, and supports both CPU and GPU for enhanced performance. To fund further development and community growth, Silentis will issue a BSC-based utility token. This token will enable decentralized governance, incentivize contributions, and provide access to premium features.

Problem Statement

Many AI tools require constant internet connectivity, exposing user data to potential breaches. Existing AI models are often too large or resource-intensive for everyday users. Traditional AI platforms are controlled by centralized entities, limiting transparency and user autonomy.

Solution

Silentis addresses these issues with:

Key Features

Tokenomics

The Silentis Token (SILENTIS) is designed exclusively to support the development and maintenance of free, privacy-focused software. It will not be used for staking, governance, or any other utilities.

Roadmap

Phase 1 (Q1 2025): Complete the launch of the Silentis Project.
Phase 2 (Q2 2025): Launch the Support Token, preview v1.0, and release an open-source Python plugin.
Phase 3 (Q3 2025): Implement additional models and introduce an advanced setup.
Phase 4 (Q4 2025): Launch the Advanced Offline AI for Enterprise on server-grade equipment.

Conclusion

Silentis aims to democratize access to AI by providing a privacy-focused, offline solution powered by Llama 3.2 4B. Through the issuance of a BSC token, Silentis ensures sustainable funding for long-term growth while maintaining its commitment to free and open software.